AI Infrastructure & Architecture
A solid foundation for AI.
We design model, data and application layers around your requirements. Hosting, access and monitoring decisions are considered together to prepare AI systems for operation.
Your defined infrastructure boundary
Access records · Evaluation · Resource tracking
Is this service right for you?
01You need clear boundaries for data and model hosting.
02You are moving from prototype to a manageable production environment.
03You need visibility into access, cost and system health.
01 /
What this service covers
01Model and hosting architectureChoose the right environment.
Model and hosting architecture
We design model serving and hosting around workloads and data requirements.
Work involved
- Model architecture
- Cloud, on-premise and hybrid options
- Deployment planning
What you receive
A target architecture and deployment approach.
02Data and search infrastructureBuild the knowledge-access layer.
Data and search infrastructure
We assess data preparation, indexing and search components together.
Work involved
- Vector databases
- Data processing and indexing
- Search infrastructure
What you receive
Infrastructure with defined data flows and search components.
03Access and securityMake boundaries part of the architecture.
Access and security
We define user, service and data permissions.
Work involved
- Access control
- Data and security architecture
- Environment and service separation
What you receive
An access model and configuration documentation.
04Monitoring and evaluationUnderstand system behavior.
Monitoring and evaluation
We design visibility into system health, answer quality and resource use.
Work involved
- Observability
- Evaluation infrastructure
- Capacity and cost visibility
What you receive
A monitoring approach and operational checklist.
02 / Example in practice
AI within your infrastructure
Illustrative scenario; not a client project.
- 01
Need
Sensitive documents need to be processed within defined infrastructure boundaries.
- 02
Approach
We design model serving, search, identity and application layers within those boundaries.
- 03
Resulting structure
Data paths and permissions are documented, with explicit operational requirements.
03 /
How we work
- 01
Requirements
Define data boundaries and workloads.
- 02
Architecture
Assess hosting and component options.
- 03
Setup
Prepare environments and access configuration.
- 04
Validation
Check monitoring and operational scenarios.
04 /
Concrete outputs
Deliverable details and scope are agreed during discovery around your needs.
- 01
A target architecture and deployment approach.
- 02
Infrastructure with defined data flows and search components.
- 03
An access model and configuration documentation.
- 04
A monitoring approach and operational checklist.
05 /
Frequently asked questions
Can every model run on-premise?
No. Licensing, hardware requirements and serving options vary. We evaluate suitable options against your needs.
Do you recommend cloud or on-premise?
We consider data constraints, workload, team capacity and cost together. Hybrid architectures are also an option.
Can you assess our existing AI infrastructure?
We can review architecture, access and operational needs to identify improvement areas.
AI Infrastructure & Architecture
Let’s define the next step.
Share your current situation and priorities so we can find a suitable starting point together.